Sea Island cotton (Gossypium barbadense) is the source of the world's finest fibre quality cotton, yet relatively little is understood about genetic variations among diverse germplasms, genes underlying important traits and the effects of pedigree selection. Here, we resequenced 336 G. barbadense accessions and identified 16 million SNPs. Phylogenetic and population structure analyses revealed two major gene pools and a third admixed subgroup derived from geographical dissemination and interbreeding. We conducted a genome-wide association study (GWAS) of 15 traits including fibre quality, yield, disease resistance, maturity and plant architecture. The highest number of associated loci was for fibre quality, followed by disease resistance and yield. Using gene expression analyses and VIGS transgenic experiments, we confirmed the roles of five candidate genes regulating four key traits, that is disease resistance, fibre length, fibre strength and lint percentage. Geographical and temporal considerations demonstrated selection for the superior fibre quality (fibre length and fibre strength), and high lint percentage in improving G. barbadense in China. Pedigree selection breeding increased Fusarium wilt disease resistance and separately improved fibre quality and yield. Our work provides a foundation for understanding genomic variation and selective breeding of Sea Island cotton.
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http://dx.doi.org/10.1111/pbi.13747 | DOI Listing |
J Texture Stud
February 2025
Institute for Advanced Biosciences, Keio University, Tsuruoka, Japan.
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January 2025
Department of Plant and Soil Sciences, University of Pretoria, Hatfield, 0001, Pretoria, South Africa.
In recent decades, natural rangelands have emerged as vital sources of livelihood and ecological services, particularly in Southern Africa, supporting communities in developing regions. However, the escalating global demand for food, driven by a growing human population, has led to the extensive expansion of cultivated areas, resulting in continuous nutrient leaching in rangelands. To ensure the long-term viability of these ecosystems, there is a need to develop effective approaches for managing and monitoring the seasonality of forage quality.
View Article and Find Full Text PDFLight Sci Appl
January 2025
State Key Laboratory of Optical Fiber and Cable Manufacture Technology, Institute of Nanoscience and Applications, Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China.
Colloidal quantum dots (CQDs) are attractive gain media due to their wavelength-tunability and low optical gain threshold. Consequently, CQD lasers, especially the surface-emitting ones, are promising candidates for display, sensing and communication. However, it remains challenging to achieve a low-threshold surface-emitting CQD laser array with high stability and integration density.
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December 2024
Department of Electrical and Electronic Engineering, Pabna University of Science and Technology, Pabna, 6600, Pabna, Bangladesh.
Methanol (CH₃OH) is a volatile, transparent, and toxic substance widely used in chemical substrates, antifreeze, and industrial applications. Ethanol (C₂H₅OH), in contrast, is commonly used in alcoholic beverages, as a fuel additive, and as an antiseptic. Differentiating between methanol and ethanol is critical due to the severe health risks associated with methanol ingestion, while ethanol is safe for consumption in moderation.
View Article and Find Full Text PDFFront Plant Sci
December 2024
School of Information Technology (IT) and Engineering, Melbourne Institute of Technology, Melbourne, VIC, Australia.
Introduction: Cotton, being a crucial cash crop globally, faces significant challenges due to multiple diseases that adversely affect its quality and yield. To identify such diseases is very important for the implementation of effective management strategies for sustainable agriculture. Image recognition plays an important role for the timely and accurate identification of diseases in cotton plants as it allows farmers to implement effective interventions and optimize resource allocation.
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